# Statistics in NumPy

Learn how to analyze different statistical distributions using NumPy.

Start## Key Concepts

Review core concepts you need to learn to master this subject

NumPy’s Mean and Axis

Conditions in Numpy.mean()

NumPy Percentile Function

NumPy’s Percentile and Quartiles

NumPy’s Sort Function

Definition of Percentile

Datasets and their Histograms

Normal Distribution using Python Numpy module

NumPy’s Mean and Axis

NumPy’s Mean and Axis

```
We will use the following 2-dimensional array for this example:
```
py
ring_toss = np.array([[1, 0, 0],
[0, 0, 1],
[1, 0, 1]])
```
The code below will calculate the average of each row.
```py
np.mean(ring_toss, axis=1)
# Output: array([ 0.33333333, 0.33333333, 0.66666667])
```
```

In a two-dimensional array, you may want the mean of just the rows or just the columns. In Python, the NumPy `.mean()`

function can be used to find these values. To find the average of all rows, set the axis parameter to 1. To find the average of all columns, set the axis parameter to 0.

## What you'll create

Portfolio projects that showcase your new skills

## How you'll master it

Stress-test your knowledge with quizzes that help commit syntax to memory